Neuronal Autocorrelation and Chosen Value Correlates in Macaque Prefrontal Cortex

Comprising neurophysiological data from macaque prefrontal cortex neurons, investigating the relationship between resting-state autocorrelation structure and chosen value correlates during reward-guided decision making. The data was collected by Sean E. Cavanagh and published in 2020 under a CC0 license. Specific details on row count, column count, and file formats are unavailable.

Use Cases

• Analyze the relationship between resting-state spike rate autocorrelation structure and the strength of chosen value correlates across individual neurons.
• Investigate how neurons with protracted resting temporal receptive fields sustain coding of chosen value from choice through reward delivery.
• Model variability in temporal specialization across prefrontal cortex neurons to predict their involvement in specific decision-making computations.

Strengths

• Data is associated with a published scientific study investigating a specific neural mechanism.
• The dataset is openly available under a permissive CC0 1.0 license.
• Focuses on a specific species (Macaca mulatta) and brain region (prefrontal and orbitofrontal cortex).

Limitations

• The dataset's structure, including row count, column names, and file formats, is unknown, hindering immediate usability.
• Sample size and data completeness cannot be assessed from the provided information.
• Data is from a single study, which may limit generalizability to other species or experimental paradigms.

Provenance

Source

Dryad digital repository.

Collection Method

Neurophysiological recordings from macaque prefrontal cortex neurons during rest and reward-guided choice tasks.

Freshness

Last updated on 2020-06-30.